Reference : FASTGAPFILL: Efficient gap filling in metabolic networks
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/17458
FASTGAPFILL: Efficient gap filling in metabolic networks
English
Thiele, Ines mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Vlassis, Nikos [> >]
Fleming, Ronan MT mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
2014
Bioinformatics
Oxford University Press - Journals Department
30
17
2529-2531
Yes (verified by ORBilu)
International
1367-4803
1460-2059
Oxford
United Kingdom
[en] Motivation: Genome-scale metabolic reconstructions summarize current knowledge about a target organism in a structured manner and as such highlight missing information. Such gaps can be filled algorithmically. Scalability limitations of available algorithms for gap filling hinder their application to compartmentalized reconstructions.
Results:We present FASTGAPFILL, a computationally efficient,tractable extension to the COBRA toolbox that permits theidentification of candidate missing knowledge from a universal biochemical reaction database (e.g., KEGG) for a given (compart-mentalized) metabolic reconstruction. The stoichiometric consistency of the universal reaction database and of the metabolic reconstruction can be tested for permitting the computation of biologically more
relevant solutions. We demonstrate the efficiency and scalability of fastGapFill on a range of metabolic reconstructions.
Luxembourg Centre for Systems Biomedicine (LCSB): Molecular Systems Physiology (Thiele Group) ; Luxembourg Centre for Systems Biomedicine (LCSB): Machine Learning (Vlassis Group) ; Luxembourg Centre for Systems Biomedicine (LCSB): Systems Biochemistry (Fleming Group)
http://hdl.handle.net/10993/17458
10.1093/bioinformatics/btu321
http://bioinformatics.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=24812336

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